wraggster
April 17th, 2012, 12:25
Scientists, engineers and software developers are always looking for innovative ways to accelerate applications and shorten computational cycles. SoftLayer (http://www.softlayer.com/) is looking to help them out by offering a new HPC cloud-based solution consisting of dedicated servers leveraging the latest GPU (Graphics Processing Unit) cards from Nvidia (http://www.nvidia.com/object/preconfigured-clusters.html).
SoftLayer’s new offering provides an on-demand, consumptive billing model for High-Performance Computing (HPC) users looking to meet the most compute intensive environments. These environments include traditional HPC fields such as data mining, numerical and seismic analysis as well advertising agencies and web design shops looking to develop interactive games, applications and 3D content.
“Using GPUs for running applications is an emerging trend in HPC today. Computing requirements continue to skyrocket but users remain as demanding as ever. They want capacity on-demand and prefer to pay only for what they use. It is incumbent on hosters to deliver this capacity in a cloud-like fashion if they want to break into this market,” said Philbert Shih, Managing Director, Structure Research Ltd. “Giving people the ability to scale GPU resources adds incredible flexibility in the way research, engineering and development projects are conducted. By putting such raw computational power into a user’s hands, in an easy pay as you go model, the focus is on research results not acquiring or maintaining the latest technology.”
SoftLayer’s new HPC hosting solution consists of dual-processor Intel E5-2600 (Sandy Bridge) based servers supporting one or two Nvidia Tesla M2090 GPUs. GPUs work in conjunction with the server’s CPU to accelerate application and processing performance. The GPU will offload compute intensive portions of the application from the CPU to accelerate overall performance of the machine, dramatically boosting application performance by running in tandem with the CPU. As a result, SoftLayer users will see a massive performance boost and HPC applications accelerated by as much as ten times.
“We are offering breakthrough performance in a unique delivery model,” said Duke Skarda, Chief Technology Officer of SoftLayer. “The beauty of this solution is the way users can break down to toughest computational problems and largest blocks of data to work them in parallel over our network driving quicker results. GPU technology is still in its infancy but customer demand continues to soar as more and more HPC applications get migrated over to cloud infrastructures.”
“Infrastructure as a Service (IaaS) providers like SoftLayer are pushing the technological envelope by making the latest technology accessible and scalable through a cloud offering,” said Sumit Gupta, General Manager of Tesla HPC at Nvidia. “This technology is all about performance without compromise and we found a partner in SoftLayer committed to enabling cloud computing services that enable GPU computing from anywhere around the world.”
Key features and benefits:
Cost effective HPC (ideal for scientific and technical computing)
Massive compute performance increase while accelerating application speeds by up to 10x
Cluster management and GPU monitoring
Parallel compute environment operates invisibly to the user
GPUs specifically designed to work as computational accelerators
SoftLayer’s new offering provides an on-demand, consumptive billing model for High-Performance Computing (HPC) users looking to meet the most compute intensive environments. These environments include traditional HPC fields such as data mining, numerical and seismic analysis as well advertising agencies and web design shops looking to develop interactive games, applications and 3D content.
“Using GPUs for running applications is an emerging trend in HPC today. Computing requirements continue to skyrocket but users remain as demanding as ever. They want capacity on-demand and prefer to pay only for what they use. It is incumbent on hosters to deliver this capacity in a cloud-like fashion if they want to break into this market,” said Philbert Shih, Managing Director, Structure Research Ltd. “Giving people the ability to scale GPU resources adds incredible flexibility in the way research, engineering and development projects are conducted. By putting such raw computational power into a user’s hands, in an easy pay as you go model, the focus is on research results not acquiring or maintaining the latest technology.”
SoftLayer’s new HPC hosting solution consists of dual-processor Intel E5-2600 (Sandy Bridge) based servers supporting one or two Nvidia Tesla M2090 GPUs. GPUs work in conjunction with the server’s CPU to accelerate application and processing performance. The GPU will offload compute intensive portions of the application from the CPU to accelerate overall performance of the machine, dramatically boosting application performance by running in tandem with the CPU. As a result, SoftLayer users will see a massive performance boost and HPC applications accelerated by as much as ten times.
“We are offering breakthrough performance in a unique delivery model,” said Duke Skarda, Chief Technology Officer of SoftLayer. “The beauty of this solution is the way users can break down to toughest computational problems and largest blocks of data to work them in parallel over our network driving quicker results. GPU technology is still in its infancy but customer demand continues to soar as more and more HPC applications get migrated over to cloud infrastructures.”
“Infrastructure as a Service (IaaS) providers like SoftLayer are pushing the technological envelope by making the latest technology accessible and scalable through a cloud offering,” said Sumit Gupta, General Manager of Tesla HPC at Nvidia. “This technology is all about performance without compromise and we found a partner in SoftLayer committed to enabling cloud computing services that enable GPU computing from anywhere around the world.”
Key features and benefits:
Cost effective HPC (ideal for scientific and technical computing)
Massive compute performance increase while accelerating application speeds by up to 10x
Cluster management and GPU monitoring
Parallel compute environment operates invisibly to the user
GPUs specifically designed to work as computational accelerators